Basically, many different graphs can be produced from hourly weather data sets. Of initial importance, however, is the visualisation of both seasonal and diurnal trends in the data. These can be displayed by graphing weeks of the year in one direction, in this case the X axis, and hours of the day along the adjacent Y axis. Variations in level within the selected data is then displayed using a colour intensity and, in the case of the three-dimensional graphs used here, as a displacement in the Z axis.

Figure 1 – An example 3D temperature plot showing seasonal and diurnal trends over the entire year.

The above graph shows an example plot of annual temperature data, displayed as weekly averages. This plot clearly shows the traditional 'saddle' shape characteristic of climates in the southern hemisphere with a significant seasonal variation in temperature. The plot also shows daily or diurnal temperature variation along the 'Hours' axis. In this case the lowest temperatures in January (weeks 1 to 4) occur early in the morning but rise to almost 40°C at midday and in the early afternoon.

These graphs can be used to display annual temperature, humidity, solar radiation, wind speed and rainfall. The table below provides links to a range of different climate data sets displayed in this format. It might be useful to browse through several of them simply to get an idea of the major patterns visible in this type of graph. For a more lengthy comparison of climates using these graphs, see also the Climates of Western Australia topic.

EXAMPLE 3D CLIMATE DATA SETS

• Alice Springs (Australia)
• London (England)
• Athens (Greece)
• Moscow (Russia)
• Copenhagen (Denmark)
• New York (USA)
• Glasgow (Scotland)
• Nairobi (Kenya)
• Hong Kong (China)
• Rome (Italy)
• Houston (USA)
• Singapore
• Kuching (Malaysia)
• Toronto (Canada)

Linear Hourly Plots

The same data as displayed above can also be plotted as a 2D linear graph. Whilst this form shows the range of diurnal variation, it does not illustrate the diurnal patterns present in the data in the same way the 3D graph does.

Figure 2 – A 2D plot of temperature over the entire year.

The three lines running through the data simply show the average maximum, the overall average and the average minimum value. These graphs can be used to show temperature, humidity, solar radiation, wind speed and rainfall.

You can use the interactive image below to compare the annual temperature characteristics of a range of different locations.

Figure 3 – Annual temperatures for a range of different climates.

Select Location: :: Alice Springs, Australia :: Kuching, Malaysia :: Nairobi, Kenya :: Houston, USA :: New York, USA :: London, UK

Wind Direction

Hourly wind direction can also be displayed, if it is present in the data. For a more detailed description of this chart, see the wind direction topic.

Figure 4 – An example annual wind direction/frequency plot.

Psychrometric Distribution

Given hourly values for temperature and relative humidity, it is possible to plot their distribution on the Psychrometric Chart. This is very useful as it clearly shows the range of conditions to be accommodated within that climate. Once plotted, a range of information can be overlayed on the chart. The chart below, for example, shows the areas most suitable for different cooling strategies.

Figure 5 – Annual hourly air conditions plotted on the Psychrometric Chart overlayed with cooling strategies.

Much work has been done by a number of researchers relating comfort parameters on the Psychrometric Chart. The result is that the comfort effects of a wide range of passive and active design techniques can be calculated via psychrometrics. This is discussed in detail in the passive design strategies topic.

Solar Position

It is always useful to see the variation in Sun position throughout the year in order to appreciate the need for shading. A sun-path diagram can be generated for any location from its latitude, longitude and time-zone. Of more importance, however, is the ability to relate aspects of the climate data to the position of the Sun, to see where the Sun is when it is the hottest or during the strongest winds, etc.

Figure 6 - Annual direct solar radiation displayed on a stereographic sun-path diagram, relating maximum radiation values to the azimuth and altitude of the Sun.

Additionally, the effects of orientation on incident solar radiation are also very important at a pre-design phase. Given hourly data for both direct and indirect solar radiation, it is a relatively simply matter to determine total annual solar collection. However, the design aim is slightly more complex as in most climates it is desirable to minimise solar collection during summer, when it is usually too hot anyway, and maximise it in winter to provide additional heating. To do this effectively, the seasonal variation in incident solar radiation must be visualised.

Figure 7 – The annual total daily incidence of solar radiation on a 1m² vertical surface at any orientation.

Figure 7 above shows the total daily collection of unobstructed direct and diffuse solar radiation on a 1m² vertical surface facing directly North (0.0°). The bright yellow line shows the running monthly average (±15 days) whilst the thinner olive lines show the actual daily collection, clearly highlighting the effects of variant cloud cover. The blue area represent the coldest three months whilst the red area represents the warmest three months.

In the Weather Tool, it is possible to interactively change the orientation of this surface and see the resulting solar collection in real time. This is accessed through the Solar Radiation button in the Solar Position panel.

The best orientation is the one that maximises the amount of incident energy in the blue period whilst minimising it in the red. See the optimum orientation topic for information on how this idea can be used to automatically derive the most appropriate compromise.

Related Topics

Wind direction can also be displayed. See the wind direction topic for a detailed discussion.